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RichardErkhov/EmbeddedLLM_-_Mistral-7B-Merge-14-v0.3-gguf

sourceHugging Faceupdated 2y agoView on Hugging Face
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Quantization made by Richard Erkhov.

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Mistral-7B-Merge-14-v0.3 - GGUF

  • —Model creator: https://huggingface.co/EmbeddedLLM/
  • —Original model: https://huggingface.co/EmbeddedLLM/Mistral-7B-Merge-14-v0.3/
NameQuant methodSize
Mistral-7B-Merge-14-v0.3.Q2_K.ggufQ2_K2.53GB
Mistral-7B-Merge-14-v0.3.IQ3_XS.ggufIQ3_XS2.81GB
Mistral-7B-Merge-14-v0.3.IQ3_S.ggufIQ3_S2.96GB
Mistral-7B-Merge-14-v0.3.Q3_K_S.ggufQ3KS2.95GB
Mistral-7B-Merge-14-v0.3.IQ3_M.ggufIQ3_M3.06GB
Mistral-7B-Merge-14-v0.3.Q3_K.ggufQ3_K3.28GB
Mistral-7B-Merge-14-v0.3.Q3_K_M.ggufQ3KM3.28GB
Mistral-7B-Merge-14-v0.3.Q3_K_L.ggufQ3KL3.56GB
Mistral-7B-Merge-14-v0.3.IQ4_XS.ggufIQ4_XS3.67GB
Mistral-7B-Merge-14-v0.3.Q4_0.ggufQ4_03.83GB
Mistral-7B-Merge-14-v0.3.IQ4_NL.ggufIQ4_NL3.87GB
Mistral-7B-Merge-14-v0.3.Q4_K_S.ggufQ4KS3.86GB
Mistral-7B-Merge-14-v0.3.Q4_K.ggufQ4_K4.07GB
Mistral-7B-Merge-14-v0.3.Q4_K_M.ggufQ4KM4.07GB
Mistral-7B-Merge-14-v0.3.Q4_1.ggufQ4_14.24GB
Mistral-7B-Merge-14-v0.3.Q5_0.ggufQ5_04.65GB
Mistral-7B-Merge-14-v0.3.Q5_K_S.ggufQ5KS4.65GB
Mistral-7B-Merge-14-v0.3.Q5_K.ggufQ5_K4.78GB
Mistral-7B-Merge-14-v0.3.Q5_K_M.ggufQ5KM4.78GB
Mistral-7B-Merge-14-v0.3.Q5_1.ggufQ5_15.07GB
Mistral-7B-Merge-14-v0.3.Q6_K.ggufQ6_K5.53GB
Mistral-7B-Merge-14-v0.3.Q8_0.ggufQ8_07.17GB

Original model description: --- license: apache-2.0 language:

  • —en tags:
  • —merge base_model:
  • —mistralai/Mistral-7B-Instruct-v0.2
  • —ehartford/dolphin-2.2.1-mistral-7b
  • —SciPhi/SciPhi-Mistral-7B-32k
  • —ehartford/samantha-1.2-mistral-7b
  • —Arc53/docsgpt-7b-mistral
  • —HuggingFaceH4/zephyr-7b-beta
  • —meta-math/MetaMath-Mistral-7B
  • —Open-Orca/Mistral-7B-OpenOrca
  • —openchat/openchat-3.5-1210
  • —beowolx/MistralHermes-CodePro-7B-v1
  • —TIGER-Lab/MAmmoTH-7B-Mistral
  • —teknium/OpenHermes-2.5-Mistral-7B
  • —Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
  • —mlabonne/NeuralHermes-2.5-Mistral-7B ---

Update 2024-01-03

Check out our v0.4 model which is based on this and achieves better average score of 71.19 versus 69.66.

Model Description

This is an update to EmbeddedLLM/Mistral-7B-Merge-14-v0.2 that removes potentially TruthfulQA-contaminated models and non-commercially licensed models:

  1. 1.berkeley-nest/Starling-LM-7B-alpha
  2. 2.Q-bert/MetaMath-Cybertron-Starling
  3. 3.v1olet/v1olet_marcoroni-go-bruins-merge-7B

This is an experiment to test merging 14 models using DARE TIES 🦙

The result is a base model that performs quite well but may need some further chat fine-tuning.

The 14 models are as follows:

  1. 1.mistralai/Mistral-7B-Instruct-v0.2
  2. 2.ehartford/dolphin-2.2.1-mistral-7b
  3. 3.SciPhi/SciPhi-Mistral-7B-32k
  4. 4.ehartford/samantha-1.2-mistral-7b
  5. 5.Arc53/docsgpt-7b-mistral
  6. 6.HuggingFaceH4/zephyr-7b-beta
  7. 7.meta-math/MetaMath-Mistral-7B
  8. 8.Open-Orca/Mistral-7B-OpenOrca
  9. 9.openchat/openchat-3.5-1210
  10. 10.beowolx/MistralHermes-CodePro-7B-v1
  11. 11.TIGER-Lab/MAmmoTH-7B-Mistral
  12. 12.teknium/OpenHermes-2.5-Mistral-7B
  13. 13.Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
  14. 14.mlabonne/NeuralHermes-2.5-Mistral-7B

Open LLM Leaderboard

v0.3v0.4
Average69.6671.19
ARC65.9666.81
HellaSwag85.2986.15
MMLU64.3565.10
TruthfulQA57.8058.25
Winogrande78.3080.03
GSM8K66.2670.81

Chat Template

We tried ChatML and Llama-2 chat template, but feel free to try other templates.

Merge Configuration

The merge config file for this model is here:

yaml
models:
  - model: mistralai/Mistral-7B-v0.1
    # no parameters necessary for base model
  - model: ehartford/dolphin-2.2.1-mistral-7b
    parameters:
      weight: 0.08
      density: 0.4
  - model: SciPhi/SciPhi-Mistral-7B-32k
    parameters:
      weight: 0.08
      density: 0.4
  - model: ehartford/samantha-1.2-mistral-7b
    parameters:
      weight: 0.08
      density: 0.4
  - model: Arc53/docsgpt-7b-mistral
    parameters:
      weight: 0.08
      density: 0.4
  - model: HuggingFaceH4/zephyr-7b-beta
    parameters:
      weight: 0.08
      density: 0.4
  - model: meta-math/MetaMath-Mistral-7B
    parameters:
      weight: 0.08
      density: 0.4
  - model: Open-Orca/Mistral-7B-OpenOrca
    parameters:
      weight: 0.08
      density: 0.4
  - model: openchat/openchat-3.5-1210
    parameters:
      weight: 0.08
      density: 0.4
  - model: beowolx/MistralHermes-CodePro-7B-v1
    parameters:
      weight: 0.08
      density: 0.4
  - model: TIGER-Lab/MAmmoTH-7B-Mistral
    parameters:
      weight: 0.08
      density: 0.4
  - model: teknium/OpenHermes-2.5-Mistral-7B
    parameters:
      weight: 0.08
      density: 0.4
  - model: Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
    parameters:
      weight: 0.08
      density: 0.4
  - model: mlabonne/NeuralHermes-2.5-Mistral-7B
    parameters:
      weight: 0.08
      density: 0.4
  - model: mistralai/Mistral-7B-Instruct-v0.2
    parameters:
      weight: 0.08
      density: 0.5
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  int8_mask: true
dtype: bfloat16